// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

#include "glog/logging.h"
#include "omp.h"
#include "opencv2/core.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/imgproc.hpp"
#include <chrono>
#include <iomanip>
#include <iostream>
#include <ostream>
#include <vector>

#include <cstring>
#include <fstream>
#include <numeric>

#include <include/config.h>
#include <include/ocr_det.h>
#include <include/ocr_rec.h>

using namespace std;
using namespace cv;
using namespace PaddleOCR;

int main(int argc, char** argv) {
	if (argc < 3) {
		std::cerr << "[ERROR] usage: " << argv[0]
			<< " configure_filepath image_path\n";
		exit(1);
	}
	std::cout << "000000  " << std::endl;
	OCRConfig config(argv[1]);
	std::cout << "111111  " << std::endl;
	config.PrintConfigInfo();
	std::cout << "222222  " << std::endl;
	std::string img_path(argv[2]);

	cv::Mat srcimg = cv::imread(img_path, cv::IMREAD_COLOR);

	DBDetector det(config.det_model_dir, config.use_gpu, config.gpu_id,
		config.gpu_mem, config.cpu_math_library_num_threads,
		config.use_mkldnn, config.max_side_len, config.det_db_thresh,
		config.det_db_box_thresh, config.det_db_unclip_ratio,
		config.visualize, config.use_tensorrt, config.use_fp16);

	Classifier* cls = nullptr;
	if (config.use_angle_cls == true) {
		cls = new Classifier(config.cls_model_dir, config.use_gpu, config.gpu_id,
			config.gpu_mem, config.cpu_math_library_num_threads,
			config.use_mkldnn, config.cls_thresh,
			config.use_tensorrt, config.use_fp16);
	}

	CRNNRecognizer rec(config.rec_model_dir, config.use_gpu, config.gpu_id,
		config.gpu_mem, config.cpu_math_library_num_threads,
		config.use_mkldnn, config.char_list_file,
		config.use_tensorrt, config.use_fp16);

	auto start = std::chrono::system_clock::now();
	std::vector<std::vector<std::vector<int>>> boxes;
	det.Run(srcimg, boxes);
	JsonObjectBuilder builder;
	rec.Run(boxes, srcimg, cls, builder);
	auto end = std::chrono::system_clock::now();
	auto duration =
		std::chrono::duration_cast<std::chrono::microseconds>(end - start);
	std::cout << "Cost  "
		<< double(duration.count()) *
		std::chrono::microseconds::period::num /
		std::chrono::microseconds::period::den
		<< "s" << std::endl;

	return 0;
}
